Multi-element antenna arrays with digital beamforming capability offer options for receiving one or more simultaneous transmissions. Some standard DBF methods rely on first and second order statistics, that is, a cross correlation vector and covariance matrix. The minimum mean squared error (MMSE) method utilizes cross correlation vectors and covariance matrices to calculate a weight vector in order to minimize signal to noise plus interference (SINR) from a combined signal. The MMSE weight vector can be calculated,w=Rx−1rxy,where the covariance is denoted Rx and cross correlation rxy.
Calculating a covariance matrix is processor and system intensive. Signals arriving at each element must be correlated with all other signals. To obtain accurate statistics, the correlation length can be relatively long, particularly in the presence of significant co-channel interference in networks allowing multiple simultaneous transmission/reception. For example, in an array of Nelement elements (assuming Hermitian symmetry) calculating the upper triangle and diagonal of the covariance requires Ncov—corr results in:Ncov—corr=Nelement^2/2+Nelement/2.For a 4×4 array of 16 elements, this requires 136 correlations of receive signals.
Depending on the array size and correlation duration, calculating the covariance matrix can require significant hardware capability (e.g. multipliers and/or memory). Also, since all signals must be available to correlate with all other signals, a common processor or complicated multiplexing system would be required.
Additionally, calibrating a phased array antenna can be challenging. Depending on the accuracy required of the calibration and the components that affect calibration, either multi-dimensional lookup tables and/or ‘realtime’ calibration are necessary. Some examples of calibration issues include changes with time, temperature, frequency, gain, and direction of arrival (DOA) and mutual coupling. A system and apparatus requiring neither significant hardware capability (common processor or complicated multiplexing) nor antenna calibration would be beneficial. Although the MMSE method does not require calibration, other methods, such as those that rely on pointing and null placement typically require calibration. Calibration errors can significantly affect the depth of a null placed on a given transmit source.
A combining technique that does not require calibration or calculation of a covariance matrix would be valuable.